DeepImageJ is a user-friendly plugin that enables the use of a variety of pre-trained deep learning models in ImageJ. The plugin bridges the gap between deep learning and standard life-science applications. DeepImageJ runs image-to-image operations on a standard CPU-based computer and does not require any deep learning expertise.
Go to releases (https://github.com/deepimagej/deepImagej-ij2-plugin/releases) and download the last version of the plugin:
- The ZIP file (DeepImageJ2_1.0.0.zip) is a plugin for ImageJ or Fiji. It contains all the necessary libraries (JAR files) and DeepImageJ2_X.X.X.jar to load and run TensorFlow models on any OS: Windows, Mac OSX, Linux.
Unzip the ZIP file and store the 5 JAR files into the plugins folder of ImageJ or Fiji.
Create the folder models inside ImageJ/Fiji directory (".../ImageJ/models/").
Download a bundled model (https://deepimagej.github.io/deepimagej/models.html), unzip it into the directory 'models' and run it over your image!
Operating systems (same requirements as for ImageJ/Fiji software).
- Windows
- Mac OSX
- Linux.
The java libraries insided ImageJ/Fiji needed to run this plugin are:
- libtensorflow-1.12.0
- libtensorflow_jni-1.12.0
- proto-1.2.0
- protobuf-java-3.2.0
The DeepImageJ project is an open source software (OSS) under the BSD 2-Clause License. All the resources provided here are freely available.
As a matter of academic integrity, we strongly encourage users to include adequate references whenever they present or publish results that are based on the resources provided here.
Cite the appropriate TensorFlow network which is bundled into DeepImageJ.
E. Gómez-de-Mariscal, C. García-López-de-Haro, L. Donati, M. Unser, A. Muñoz-Barrutia, D. Sage, "DeepImageJ: A user-friendly plugin to run deep learning models in ImageJ" BioRxiv, 2019. https://www.biorxiv.org/content/10.1101/799270v2